How Backpropagation Works Step-by-Step in ANN | How AI Models Learn from Errors in Deep Learning

Описание: In this video, you will learn Backpropagation in Artificial Neural Networks in the simplest and most practical way. If you are a Machine Learning or Deep Learning student and you are confused about how neural networks actually learn, this video is for you.

We will understand what Backpropagation is, why it is needed, and how it works step-by-step. You will see how error is calculated, how gradients are computed using the chain rule, and how weights are updated using gradient descent.

This video covers:

Forward propagation

Loss function

Chain rule explanation

Gradient calculation

Weight updates

Training loop process

If you are preparing for interviews, building ML projects, or studying Deep Learning seriously, understanding Backpropagation is mandatory.

This is not a short explanation. This is a complete deep dive designed for students who want real understanding.


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